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This paper investigates the potential of ChatGPT for helping humans tackle problems that require creativity. Across five experiments, we asked participants to use ChatGPT (GPT-3.5) to generate creative ideas for various everyday and innovation-related problems, including choosing a creative gift for a teenager, making a toy, repurposing unused items and designing an innovative dining table. We found that using ChatGPT increased the creativity of the generated ideas compared with not using any technology or using a conventional Web search (Google). This effect remained robust regardless of whether the problem required consideration of many (versus few) constraints and whether it was viewed as requiring empathetic concern. Furthermore, ChatGPT was most effective at generating incrementally (versus radically) new ideas. Process evidence suggests that the positive influence of ChatGPT can be attributed to its capability to combine remotely related concepts into a cohesive form, leading to a more articulate presentation of ideas.
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http://dx.doi.org/10.1038/s41562-024-01953-1 | DOI Listing |
Int J Eat Disord
September 2025
Department of Psychology, Wesleyan University, Middletown, Connecticut, USA.
Objectives: Generative Artificial Intelligence (AI) could transform how science is conducted, supporting researchers with writing, coding, peer review, and evidence synthesis. However, it is not yet known how eating disorder researchers utilize generative AI, and uncertainty remains regarding its safe, ethical, and transparent use. The Executive Committee of the International Journal of Eating Disorders disseminated a survey for eating disorder researchers investigating their practices and perspectives on generative AI, with the goal of informing guidelines on appropriate AI use for authors, reviewers, and editors.
View Article and Find Full Text PDFAnat Sci Educ
September 2025
Department of Anatomy, Hamidiye Faculty of Medicine, University of Health Sciences, Istanbul, Turkey.
Educational materials advocating whole-body donation must be accurate, easy to read, and transparent, as one potential solution to the fact that the supply of donations is not keeping pace with educational demand, thereby disrupting anatomy education programs. The use of AI technologies to supplement communications with prospective donors and next of kin deserves investigation to determine whether LLM-based approaches meet the common requirements for effective communication. This study contributes to the limited literature on LLM-supported communications by presenting a comparative quantitative benchmark and an adaptable evaluation framework.
View Article and Find Full Text PDFAcad Radiol
September 2025
Department of Radiology, Başakşehir Çam and Sakura City Hospital, Istanbul, Turkey (E.E.).
Purpose: This study aimed to evaluate the performance of ChatGPT (GPT-4o) in interpreting free-text breast magnetic resonance imaging (MRI) reports by assigning BI-RADS categories and recommending appropriate clinical management steps in the absence of explicitly stated BI-RADS classifications.
Methods: In this retrospective, single-center study, a total of 352 documented full-text breast MRI reports of at least one identifiable breast lesion with descriptive imaging findings between January 2024 and June 2025 were included in the study. Incomplete reports due to technical limitations, reports describing only normal findings, and MRI examinations performed at external institutions were excluded from the study.
J Prof Nurs
September 2025
Kocaeli University of Health and Technology, Information Systems Engineering Deparment, Kocaeli, Turkey; Wefi Games Software Company, Goller Bolgesi Teknokenti, Isparta, Turkey.
Background: Comprehensive history-taking is crucial for patient assessment, prioritisation of care, and planning of care. While direct instruction methods effectively explain history-taking processes and components, they provide insufficient opportunities for practice, necessitating the implementation of supplementary teaching strategies.
Objective: This study aimed to examine the effects of AI chatbot-supported history-taking training on nursing students' questioning skills and clinical stress levels.
Lancet Oncol
September 2025
UT Southwestern Medical Center, Dallas, TX 75390, USA. Electronic address: